Communication for non-medication order (CNMO) is a type of free text communication order providers use for asynchronous communication about patient care. The objective of this study was to understand the extent to which non-medication orders are being used for medication-related communication. We analyzed a sample of 26 524 CNMOs placed in 6 hospitals. A total of 42% of non-medication orders contained medication information. There was large variation in the usage of CNMOs across hospitals, provider settings, and provider types. The use of CNMOs for communicating medication-related information may result in delayed or missed medications, receiving medications that should have been discontinued, or important clinical decision being made based on inaccurate information. Future studies should quantify the implications of these data entry patterns on actual medication error rates and resultant safety issues.
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http://dx.doi.org/10.1093/jamiaopen/ooaa020 | DOI Listing |
Digit Health
January 2025
The National Research Centre for The Working Environment, Copenhagen, Denmark.
Background: People with low back pain (LBP) are often recommended to self-manage their condition, but it can be challenging without support. Digital health interventions (DHIs) have shown promise in supporting self-management of LBP, but little is known about healthcare providers' (HCPs) engagement in implementing these.
Aims: We aimed to examine HCPs' engagement in patient recruitment for the selfBACK app clinical trial and explore their perceptions of the app.
JAMIA Open
February 2025
Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, ON M5B 1T8, Canada.
Objectives: Deidentification of personally identifiable information in free-text clinical data is fundamental to making these data broadly available for research. However, there exist gaps in the deidentification landscape with regard to the functionality and flexibility of extant tools, as well as suboptimal tradeoffs between deidentification accuracy and speed. To address these gaps and tradeoffs, we develop a new Python-based deidentification software, pyDeid.
View Article and Find Full Text PDFJ Paediatr Child Health
January 2025
School of Pharmacy and Medical Sciences, Griffith University, Gold Coast, Queensland, Australia.
Aim: COVID-19 has brought unprecedented challenges to the healthcare system. The rapid spread of the virus, laboratory burn-out, exhausted staff, diagnostic uncertainty and lack of guidelines cumulatively disrupted hospital antimicrobial stewardship (AMS) programs. This scoping review evaluated how the COVID-19 pandemic has impacted the implementation of AMS, particularly within the context of clinical audits.
View Article and Find Full Text PDFUrologia
January 2025
Research Center for Evidence-Based Medicine, Iranian EBM Centre: A JBI Centre of Excellence, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
This Umbrella Review aims to gather high-quality evidence on urolithiasis outcomes and complications, comparing extracorporeal shockwave lithotripsy (ESWL), ureteroscopic lithotripsy (URSL), and retrograde intrarenal surgery (RIRS). We incorporated systematic reviews, some containing meta-analyses, into two separate reports, focusing on quantitative and qualitative results. Additionally, when data permitted, a secondary meta-analysis was conducted using final effect estimates from multiple meta-analyses.
View Article and Find Full Text PDFFront Artif Intell
January 2025
Center for Cognitive Interaction Technology (CITEC), Technical Faculty, Bielefeld University, Bielefeld, Germany.
Background: In the field of structured information extraction, there are typically semantic and syntactic constraints on the output of information extraction (IE) systems. These constraints, however, can typically not be guaranteed using standard (fine-tuned) encoder-decoder architectures. This has led to the development of constrained decoding approaches which allow, e.
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